Lara J. Martin, Affiliate Assistant Professor
Dr. Lara J. Martin (she/they) is an assistant professor at the University of Maryland, Baltimore County in the CSEE department, researching human-centered artificial intelligence with a focus on improving natural language processing tools for various applications. They have worked in the areas of automated story generation, augmentative and alternative communication (AAC) tools, AI for tabletop roleplaying games, speech processing, and affective computing—publishing in top-tier conferences such as AAAI, ACL, EMNLP, and IJCAI. They have also been featured in Wired and BBC Science Focus magazine. Previously, Dr. Martin was a 2020 Computing Innovation Fellow (CIFellow) postdoctoral researcher at the University of Pennsylvania working with Dr. Chris Callison-Burch. She earned her PhD in Human-Centered Computing from the Georgia Institute of Technology, where she worked with Dr. Mark Riedl. She also has a MS in Language Technologies from Carnegie Mellon University and a BS in Computer Science & Linguistics from Rutgers University—New Brunswick.
Website: https://laramartin.net/
LinkedIn: https://www.linkedin.com/in/lara-j-martin
Sanorita Dey, Affiliate ProfessorDr. Sanorita Dey is an Assistant Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County (UMBC), with an affiliation in the Information Systems Department. Her research lies at the intersection of human-computer interaction, artificial intelligence, and computing education, where she investigates how AI can foster more reflective, transparent, and equitable human interactions. Her work focuses on designing human-centered AI systems that support aligned mentorship, reflective advising, career development, collaborative learning, and digital safety. By combining AI with insights from the learning sciences and social computing, she develops interactive technologies that help people make sense of complex information, build shared understanding, and make informed decisions in educational and professional settings. Her long-term goal is to create AI systems that strengthen human agency, trust, and meaningful collaboration while expanding access to high-quality mentoring and learning opportunities.
Abu Zaher Md. Faridee, Adjunct Assistant Professor
Dr. Faridee’s professional work and research focus on constructing scalable machine learning models resilient against domain and category shifts with minimal-to-no additional supervision. He primarily engages with deep domain adaptation, unsupervised, self-supervised, adversarial, disentangled representation learning, novel category discovery, and learnable data augmentation techniques, with practical applications in text, audio, and video domains. Dr. Faridee aims to discover the optimal transferability of representations across domains, tasks, and modalities, addressing real-world ML challenges with these methodologies.
At Amazon, Dr. Faridee’s team developed an end-to-end neural machine translation pipeline enhancing Amazon’s customer service experience. He enhanced the robustness of NMT models against noisy, out-of-domain inputs using the aforementioned approaches. In 2021, he interned with Microsoft Research’s Audio and Acoustics Research Group, devising novel deep neural architectures for estimating deep noise suppression model performance.
Before obtaining his Ph.D., Dr. Faridee spent approximately 8 years constructing, assembling, and leading teams in distributed data processing and analytics back-ends, catering to millions of users in the USA and UK. From 2009–2013, he actively contributed to several open-source NLP and ML projects through the Google Summer of Code program, both as a participant and later as a mentor.
LinkedIn: www.linkedin.com/in/azmfaridee
Anuradha Ravi, Research Assistant Professor
Dr. Ravi is a Research Assistant Professor in Information Systems at UMBC. Her research interests include edge computing, developing low-power machine learning models for IoT, IoT-enhanced smart spaces, and wireless networking. Prior to joining UMBC, Dr. Ravi worked as a Research Scientist (PostDoc) at Singapore Management University (Oct 2018 – Mar 2023). She completed her Ph.D. at the Indian Institute of Technology, Roorkee, India, in 2016. Dr. Ravi was awarded the “SMU Research Excellence” award for her contribution to the “AI-Based Occupancy Aware Smart Building Energy Optimization project,” which includes indoor localization for occupancy sensing in Smart Buildings. She has vast experience building real-time working prototypes to convert research into real-time demonstration.
Website: https://sites.google.com/view/anuradhar
LinkedIn: https://www.linkedin.com/in/anuradha-ravi-ph-d-36564a3b/
Catherine Ordun, Ph.D. ’23, information systems, Adjunct Assistant Professor
Catherine Ordun is a Vice President at Booz Allen Hamilton leading AI Rapid Prototyping in the Office of the CTO. She graduated in 2023 with a PhD from the Department of Information Systems under Dr. Sanjay Purushotham and Co-advised by Dr. Edward Raff. Her dissertation was entitled “Multimodal Deep Generative Models for Cross Spectral Image Analysis.” Her research interests combine industry innovation and AI development in Multimodal AI, biometrics, and visible-thermal image registration. At Booz Allen, she coordinates with leaders in defense, civil, and health as an AI SME to develop novel and scalable technical approaches. She has also supported the Mark Cuban AI Bootcamp since 2020, which trains high school students to learn the basics of AI. In her spare time, she writes science fiction, runs, and spends time with her family.
LinkedIn: https://www.linkedin.com/in/catherine-ordun
Philip Feldman, M.S. ’14, human-centered computing, and Ph.D. ’20, human-centered computing, Adjunct Assistant Professor
Dr. Feldman has been an Adjunct Research Assistant Professor of Information Systems at UMBC since 2020. He has a diverse and extensive professional background, having served as an AI/ML Futurist at ASRC Federal, Technology Architect at Novetta, Inc, and in various technical and leadership roles at other organizations. His educational background includes a PhD and MS in Human-Centered Computing from UMBC, an MS in Interdisciplinary Studies from Johns Hopkins University, and a BA in Interdisciplinary Studies from the University of Maryland. He has been a speaker at several prominent events and has authored the book “Stampede Theory: Human Nature, Technology, and Runaway Social Realities” published by Elsevier in 2023. Additionally, he has a rich history of publications, speaking engagements, and patents in the fields of AI, machine learning, and human-centered computing. His research interests include societal-scale AI conflict, intelligent control systems, simulation, ethics, and the impact of technology on society.
Website: https://philfeldman.com
LinkedIn: https://www.linkedin.com/in/phil-feldman-phd/
Bipendra Basnyat, M.S. ’17, information systems, and Ph.D. ’22, artificial intelligence and machine learning, Adjunct Assistant Professor
Bipendra Basnyat, P.E., PhD is a distinguished AI/ML Solutions Architect with over two decades of experience in designing and implementing advanced artificial intelligence and machine learning systems. Holding a PhD in AI/Machine Learning from the University of Maryland, Baltimore County (UMBC), dual master’s degrees in Information Systems and Civil Engineering, Dr. Basnyat brings a unique blend of academic expertise and industry knowledge to the field.
His career spans roles at prestigious companies like Deloitte, Xerox, and UnitedHealth, where he has consistently driven innovation in AI/ML applications. As an Adjunct Assistant Professor at UMBC, he continues to contribute to academia through teaching, mentoring, and research collaborations. Dr. Basnyat’s technical prowess encompasses various AI/ML frameworks, cloud technologies, and big data platforms, complemented by his entrepreneurial spirit, having founded three startups. His work has been recognized through successful NSF-funded projects and publications in reputable international conferences, particularly in Computer Vision. Currently, Dr. Basnyat is leveraging his expertise to address Human-Wildlife Conflict using AI, exemplifying his commitment to applying cutting-edge technology to real-world challenges.
LinkedIn: https://www.linkedin.com/in/bipendra-basnyat-p-e-phd-65795a2a/
Aravind Mohan, Adjunct Assistant Professor
Dr. Aravind Mohan is currently an Assistant Professor in the Department of Computer Science at McMurry University. Previously, Dr. Mohan was a faculty member at Allegheny College. He completed his Ph.D. in Computer Engineering at Wayne State University in 2017 in the Big Data Research Lab led by Dr. Shiyong Lu. Before that, he worked in the industry as a software engineer. His research focuses on big data management and cloud computing. His broader areas of interest are services computing, online education services, and information retrieval. He has published several research articles in peer-reviewed international conferences, including the IEEE conference on services computing, big data congress, big data, big data computing services and applications, and the ACM SIGIR conference. He is a member of IEEE and ACM.
Personal Website: amohan.mcm.edu
Matthias K. Gobbert, Affiliate Professor
Matthias K. Gobbert is Professor of Mathematics in the Department of Mathematics and Statistics at UMBC. He earned his Ph.D. in Mathematics from Arizona State University in 1996 and joined UMBC after one year as post-doc at the Institute for Mathematics and its Applications at the University of Minnesota. Dr. Gobbert’s research interests include scientific and parallel computing, the numerical solution of partial differential equations, industrial mathematics, and most recently data science, typically in collaboration with application scientists.
Dr. Gobbert has extensive experience in initiatives. He co-founded the Center for Interdisciplinary Research and Consulting, the UMBC High Performance Computing Facility, the REU Site: Interdisciplinary Program in High Performance Computing, the NSF initiative CyberTraining: Big Data + HPC + Atmospheric Physics at UMBC, and is now PI and co-director of the REU Site: Online Interdisciplinary Big Data Analytics in Science and Engineering. Dr. Gobbert also initiated both the departmental and the university partnerships with the University of Kassel in Kassel, Germany.
Website: https://userpages.umbc.edu/~gobbert/
Sanorita Dey, Affiliate Professor
Sudip Chakraborty, Affiliate Assistant Professor and Research Assistant Professor, iHARP
Indrajeet Ghosh, Postdoctoral Research Associate
Marilyn Iriarte, M.S. ’16, human-centered computing, Research Assistant Professor
Evelyn Marie Kempe, Ph.D. ’24, information systems, Adjunct Assistant Professor
Richard Forno, Affiliate Teaching Professor
Lara Martin, Affiliate Assistant Professor
Maloy Kyuman Devnath, Postdoctoral Research Associate
Rebecca Williams, Affiliate Professor